Technologies Assessing Limb Bradykinesia in Parkinson’s Disease

Hasan, Hasan; Athauda, Dilan; Foltynie, Thomas; Noyce, Alastair J.

doi:10.3233/jpd-160878

Cited by 58 publications

(60 citation statements)

References 82 publications

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“…1,2 To obviate these shortcomings, a range of technologies measuring bradykinesia in PD have been developed. [3][4][5][6][7][8][9][10][11][12] The BRadykinesia Akinesia Incoordination (BRAIN) test is a freely available, online keyboard finger-tapping test that is based on the alternate finger-tapping task. 13,14 It has previously been shown to differentiate patients with PD from healthy controls and has been used for the longitudinal monitoring of motor function in the PREDICT-PD study, a large cohort of healthy older individuals stratified for future risk of PD.…”

Section: Abstract: Backgroundmentioning

confidence: 99%

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The BRadykinesia Akinesia INcoordination (BRAIN) Tap Test: Capturing the Sequence Effect

Hasan

Burrows

Hellman³

et al. 2019

Movement Disord Clin Pract

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Background The BRadykinesia Akinesia INcoordination (BRAIN) tap test is an online keyboard tapping task that has been previously validated to assess upper limb motor function in Parkinson's disease (PD). Objectives To develop a new parameter that detects a sequence effect and to reliably distinguish between PD patients on and off medication. In addition, we sought to validate a mobile version of the test for use on smartphones and tablet devices. Methods The BRAIN test scores in 61 patients with PD and 93 healthy controls were compared. A range of established parameters captured number and accuracy of alternate taps. The new velocity score recorded the intertap speed. Decrement in the velocity score was used as a marker for the sequence effect. In the validation phase, 19 PD patients and 19 controls were tested using different hardware including mobile devices. Results Quantified slopes from the velocity score demonstrated bradykinesia (sequence effect) in PD patients (slope cut‐off −0.002) with 58% sensitivity and 81% specificity (discovery phase of the study) and 65% sensitivity and 88% specificity (validation phase). All BRAIN test parameters differentiated between on and off medication states in PD. Differentiation between PD patients and controls was possible on all hardware versions of the test. Conclusion The BRAIN tap test is a simple, user‐friendly, and free‐to‐use tool for the assessment of upper limb motor dysfunction in PD, which now includes a measure of bradykinesia.

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Section: Abstract: Backgroundmentioning

confidence: 99%

“…Rating scales are valuable for clinical practice and research but are prone to interrater and intrarater variability . To obviate these shortcomings, a range of technologies measuring bradykinesia in PD have been developed …”

mentioning

confidence: 99%

The BRadykinesia Akinesia INcoordination (BRAIN) Tap Test: Capturing the Sequence Effect

Hasan

Burrows

Hellman³

et al. 2019

Movement Disord Clin Pract

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“…Hence, we set to ascertain whether a natural interaction with keyboards would enable a new method to remotely detect and monitor parkinsonian motor signs nonobtrusively by analyzing the characteristics of free‐text typing. Such an approach could have advantages over existing solutions, because (1) it can extract motor information from the natural interaction of the patients or study participants with their devices without requiring active collaboration; (2) it could virtually reach any person who is typing with an internet‐connected device, opening a window on the motor skills and parkinsonian signs of an enormous number of individuals; (3) it can acquire data remotely without requiring to attend a clinic; and (4) participants could be monitored longitudinally in a quasi‐continuous manner.…”

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confidence: 99%

Remote Monitoring of Treatment Response in Parkinson's Disease: The Habit of Typing on a Computer

et al. 2019

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Objective The recent advances in technology are opening a new opportunity to remotely evaluate motor features in people with Parkinson's disease (PD). We hypothesized that typing on an electronic device, a habitual behavior facilitated by the nigrostriatal dopaminergic pathway, could allow for objectively and nonobtrusively monitoring parkinsonian features and response to medication in an at‐home setting. Methods We enrolled 31 participants recently diagnosed with PD who were due to start dopaminergic treatment and 30 age‐matched controls. We remotely monitored their typing pattern during a 6‐month (24 weeks) follow‐up period before and while dopaminergic medications were being titrated. The typing data were used to develop a novel algorithm based on recursive neural networks and detect participants’ responses to medication. The latter were defined by the Unified Parkinson's Disease Rating Scale‐III (UPDRS‐III) minimal clinically important difference. Furthermore, we tested the accuracy of the algorithm to predict the final response to medication as early as 21 weeks prior to the final 6‐month clinical outcome. Results The score on the novel algorithm based on recursive neural networks had an overall moderate kappa agreement and fair area under the receiver operating characteristic (ROC) curve with the time‐coincident UPDRS‐III minimal clinically important difference. The participants classified as responders at the final visit (based on the UPDRS‐III minimal clinically important difference) had higher scores on the novel algorithm based on recursive neural networks when compared with the participants with stable UPDRS‐III, from the third week of the study onward. Conclusions This preliminary study suggests that remotely gathered unsupervised typing data allows for the accurate detection and prediction of drug response in PD. © 2019 International Parkinson and Movement Disorder Society

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“…Technology-based objective measures can reduce rater bias and interrater variability and increase sensitivity, elucidating important subclinical changes [4, 7, 8]. As of November 2015, there were at least 73 different devices (22 wearable, 38 nonwearable, and 13 hybrid) developed to assess Parkinson disease (PD) [9], and, as of October 2016, at least 47 assessed limb bradykinesia specifically [10]. Among the wearable devices, only Kinesia [11], a hybrid device, and 6 other wearable devices have been used to assess PD by groups other than the developers [12-17].…”

Section: Introductionmentioning

confidence: 99%

Tablet-Based Application for Objective Measurement of Motor Fluctuations in Parkinson Disease

et al. 2018

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Background: The motor subscale of the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS-III) has limited applicability for the assessment of motor fluctuations in the home setting. Methods: To assess whether a self-administered, tablet-based application can reliably quantify differences in motor performance using two-target finger tapping and forearm pronation-supination tasks in the ON (maximal dopaminergic medication efficacy) and OFF (reemergence of parkinsonian deficits) medication states, we recruited 11 Parkinson disease (PD) patients (age, 60.6 ± 9.0 years; disease duration, 12.8 ± 4.1 years) and 11 healthy age-matched controls (age, 62.5 ± 10.5 years). The total number of taps, tap interval, tap duration, and tap accuracy were algorithmically calculated by the application, using the more affected side in patients and the dominant hand in healthy controls. Results: Compared to the OFF state, PD patients showed a higher number of taps (84.2 ± 20.3 vs. 54.9 ± 26.9 taps; p = 0.0036) and a shorter tap interval (375.3 ± 97.2 vs. 708.2 ± 412.8 ms; p = 0.0146) but poorer tap accuracy (2,008.4 ± 995.7 vs. 1,111.8 ± 901.3 pixels; p = 0.0055) for the two-target task in the ON state, unaffected by the magnitude of coexistent dyskinesia. Overall, test-retest reliability was high (r >0.75) and the discriminatory ability between OFF and ON states was good (0.60 ≤ AUC ≤ 0.82). The correlations between tapping data and MDS-UPDRS-III scores were only moderate (–0.55 to 0.55). Conclusions: A self-administered, tablet-based application can reliably distinguish between OFF and ON states in fluctuating PD patients and may be sensitive to additional motor phenomena, such as accuracy, not captured by the MDS-UPDRS-III.

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Technologies Assessing Limb Bradykinesia in Parkinson’s Disease

Cited by 58 publications

References 82 publications

The BRadykinesia Akinesia INcoordination (BRAIN) Tap Test: Capturing the Sequence Effect

The BRadykinesia Akinesia INcoordination (BRAIN) Tap Test: Capturing the Sequence Effect

Remote Monitoring of Treatment Response in Parkinson's Disease: The Habit of Typing on a Computer

Tablet-Based Application for Objective Measurement of Motor Fluctuations in Parkinson Disease

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